code: def dump_backend_state(gm, args, compiler_name, check_accuracy=False):
      """
      Dumps the dynamo graph to repro the issue.
      1) It tries to convert Fx GraphModule to a string. If we can, it writes to a
      repro.py file.
      2) If we can't convert Fx GraphModule to a string, we use to_folder to save
      the module and save a tar file.
      """
      assert NNModuleToString.can_convert_to_string(gm)
      return dump_backend_repro_as_file(
          gm, args, compiler_name, check_accuracy
      )
  
imports: import argparse
  import copy
  import functools
  import logging
  import os
  import shutil
  import sys
  import textwrap
  from importlib import import_module
  from typing import Union
  import torch
  import torch.fx
  from torch._dynamo.debug_utils import AccuracyError, backend_accuracy_fails, BUCK_CMD_PREFIX, BuckTargetWriter, extra_imports, generate_config_string, helper_for_dump_minify, InputReader, InputWriter, minifier_dir, NNModuleToString, NopInputReader, run_fwd_maybe_bwd, same_two_models
  from torch.fx.experimental.symbolic_shapes import fx_placeholder_targets
  from torch.hub import tqdm
  from ..None import config
  from ..backends.registry import lookup_backend, register_debug_backend
  from ..debug_utils import clone_inputs_retaining_gradness
label_desc: Use image node_id 4 for calling a global function with example usage: dump_backend_state(gm, args, compiler_name, check_accuracy) and returns: dump_backend_repro_as_file